By drawing on genetic data from over five million people, an international team of researchers has created a genetic test, known as a polygenic risk score (PGS), which they say can predict during early childhood the likelihood of becoming obese in adulthood. This finding could help to identify children and adolescents at higher genetic risk of developing obesity, who could benefit from lifestyle interventions or other targeted preventative strategies at a younger age.
“What makes the score so powerful is its ability to predict, before the age of five, whether a child is likely to develop obesity in adulthood, well before other risk factors start to shape their weight later in childhood,” said assistant professor Roelof Smit, MD, PhD, from the NNF Center for Basic Metabolic Research (CBMR) at the University of Copenhagen. “Intervening at this point can have a huge impact.”
Smit is first and corresponding author of the international team’s report in Nature Medicine, which is titled “Polygenic prediction of body mass index and obesity through the life course and across ancestries.” In their paper, the team concluded, “Taken together, we show that BMI PGSs can be used for prediction of adult obesity throughout the life course, particularly in early life, and for severe obesity.”
Obesity is a major public health concern that causes or exacerbates many chronic diseases and leads to reduced life expectancy, the authors wrote. “By 2035, more than half of the global population is projected to be living with overweight or obesity.” However, the team noted, treatment strategies such as intense lifestyle interventions (ILIs), bariatric surgery, and medications are not universally effective. Some are also not without risk, or will likely remain inaccessible to most people, the team stated. “Thus, preventing obesity remains paramount.”
Obesity can often manifest during childhood and tends to persist into adulthood, the authors continued. This is in contrast to many other chronic conditions. Predictors such as genetic variants, which are fixed at conception and so available during early life, could be of particular value.
The subtle variations in our genomes can greatly impact our health, they noted. A PGS is like a calculator that combines the effects of the different risk variants that a person carries and provides an overall score. “In recent years, PGSs that capture an individual’s inherited polygenic susceptibility to a trait or disease have shown great promise in enhancing disease risk prediction and population screening.” Thousands of genetic variants have been identified that increase our risk of obesity, the investigators pointed out, for example, variants that act in the brain and influence our appetite.
The newly reported study has arisen from the Genetic Investigation of Anthropometric Traits (GIANT) Consortium, an international collaboration of human genetics researchers dedicated to studying the genetic architecture of anthropometric traits such as human height and body mass index. It involved a collaboration with the consumer genetics and research company 23andMe and the contributions of more than 600 scientists from 500 institutions globally.
To create the PGS for obesity, the scientists drew on the genetic data of more than five million people—the largest and most diverse genetic dataset ever. “We used GWAS summary statistics from the GIANT consortium and 23andMe, encompassing over 5.1 million people, to create ancestry-specific and multi-ancestry PGSs capturing genetic predisposition to weight gain and obesity,” the investigators wrote in summary. They then tested their PGS on datasets of the physical and genetic characteristics of more than 500,000 people.
Their analyses suggested that the new PGS was twice as effective as the previous best test at predicting a person’s risk of developing obesity. “This new polygenic score is a dramatic improvement in predictive power and a leap forward in the genetic prediction of obesity risk, which brings us much closer to clinically useful genetic testing,” said senior author Ruth Loos, PhD, a professor from CBMR at the University of Copenhagen.
The scientists also investigated the relationship between a person’s genetic risk of obesity and the impact of lifestyle weight loss interventions, such as diet and exercise. They discovered that people with a higher genetic risk of obesity were more responsive to interventions but also regained weight more quickly when the interventions ended. “Additionally, we demonstrate the potential added value of the PGS in two distinct clinical applications: predicting adult BMI at an early age and weight change in response to ILIs,” they wrote. “Analyzing clinical trial data of ILIs, we observed that individuals with a higher PGS lost modestly more weight during the first year. However, this group was also at higher risk of weight regain after this most intensive portion of the intervention had concluded.”
The new PGS does have some limitations. Despite drawing on the genomes of a broader, more globally representative population, it was far better at predicting obesity in people with European-like ancestry than in people with African ancestry.
But overall, the investigators commented, “This PGS represents a substantial improvement compared to previous scores and may help to identify individuals at high risk to allow for timely prevention or treatment of obesity, such as through integration in a broader predictive framework jointly modelling genetic and environmental risk.”
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